The present invention relates to medical diagnostic X-ray imaging. In particular, the present invention relates to dual energy decomposition for tissue specific imaging using a computer assisted detection technique to obtain a cancellation parameter.
Today, doctors and technicians commonly have access to very sophisticated medical diagnostic X-ray imaging devices. Typically during the operation of an X-ray imaging device, an X-ray source emits X-ray photons under very controlled circumstances. The X-ray photons travel through a region of interest (ROI) of a patient under examination and impinge upon a detector. In the past, X-ray imaging devices employed rudimentary film based detectors. However, recent developments have led to solid state detectors comprised of a grid of discrete detector elements that individually respond to exposure by X-ray photons. Regardless of the detector used, however, the goal remain s the same, namely, to produce a clear resultant image of preselected structures of interest (e.g., specific types of tissues) within the ROI.
There is an inherent difficulty associated with producing a clear resultant image, however. In particular, because the X-ray photons travel through the entire patient, the image formed on the detector is a superposition of all the anatomic structures through which X-ray photons pass, including the preselected structures of interest. The superposition of anatomic structures is sometimes referred to as xe2x80x9canatomic noisexe2x80x9d. The effect of anatomic noise on the resultant image is to produce clutter, shadowing, and other obscuring effects that render the resultant image much less intelligible than the ideal clear resultant image.
Past attempts to reduce the effects of anatomic noise included, for example, xe2x80x9cdual-energyxe2x80x9d imaging. When employing dual-energy imaging, a doctor or technician acquired an image at high average X-ray photon energy, and an image at low average X-ray photon energy. Because different internal structures absorb different X-ray photon energies to different extents, it was possible to combine the two resultant images to suppress anatomic noise, according to:
xe2x80x83SB(x,y)=exp[log (H(x,y))xe2x88x92w log(L(x,y))],(0 less than w  less than 1),
where SB is the decomposed image achieved through the log subtraction at a specific cancellation parameter w, H(x,y) is an image obtained at high energy, and L(x,y) is an image obtained at low energy. By varying w, SB becomes a decomposed image of either soft tissue or of bone.
However, in the past, users of the previously mentioned decomposition technique had to vary the cancellation parameter, w, manually through trial and error. The resulting manual variation of the cancellation parameter was time consuming and hindered the workflow in the clinical environment. Furthermore, the final value chosen for the cancellation parameter was not always the one that provided the best cancellation of bone or soft tissue given the high and low energy images.
A need has long existed in the industry for a method and apparatus for dual energy decomposition that addresses the problems noted above and previously experienced.
A preferred embodiment of the present invention provides a method for determining a suggested value for a cancellation parameter for a dual energy decomposition. The method includes obtaining a first energy level image of internal structure, obtaining a second, lower, energy level image of the internal structure, and iteratively processing the images to determine a provisional value for the cancellation parameter. In particular, the iteration includes varying a cancellation parameter in a cancellation equation, obtaining a structure cancelled image from the first and second energy level images according to the cancellation equation, and evaluating a cancellation metric from the structure cancelled image. The provisional cancellation parameter may then be chosen (e.g., as the value that approximately minimizes a variance cancellation metric). Further iterations may be performed around the provisional cancellation parameter to refine the provisional cancellation parameter into a final cancellation parameter.
Similarly, the present invention may be embodied in a medical diagnostic imaging processing system. The system includes a processing circuit, and a memory coupled to the processing circuit for storing a first energy level image of internal structure and a second, lower, energy level image of the internal structure. The memory stores instructions for execution by the processor to accomplish the steps noted above. In particular, the instructions iteratively vary a cancellation parameter in a cancellation equation, obtain a structure cancelled image from the first and second energy level images according to the cancellation equation, and evaluate a cancellation metric from the structure cancelled image. The instructions then select a provisional cancellation parameter based on the cancellation metric.